零担货物序贯装箱优化问题的 遗传模拟退火算法
A Genetic and Simulated Annealing Algorithm for Optimal Sequential Casing of Less-than-Carload Freights
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摘要: 从缩小搜索区域、增强算法的收敛性以及缩短计算时间的角度出发,提出将模拟退火思想引入遗传算 法,应用遗传模拟退火算法(GSAA)求解零担货物在集装箱中的序贯装箱优化问题,阐明了该算法的具体实现过 程,包括问题编码、适应函数值计算、遗传操作、邻域选择以及降温方法等内容,并通过实际数值计算表明该算法 优于传统的计算方法。Abstract: From the angle of reducing searching region, strengthening convergence and shortening calculating time, the simulated annealing idea is introduced into the genetic algorithm to solve the optimal sequential casing problem of less-than-carload freights in containers. The specific process for realizing the algorithm is expounded, including coding, fitness function calculation, genetic operation, neighborhood selection and temperature reducing methods,etc. Practical numeric calculation shows that the algorithm is superior to the old resolutions.
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